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Baseline diabetes as a way to predict CV outcomes in a lipid-modifying trial: a meta-analysis of 330,376 patients from 47 landmark studies

Overview of attention for article published in Cardiovascular Diabetology, May 2015
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1 tweeter

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3 Dimensions

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39 Mendeley
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Title
Baseline diabetes as a way to predict CV outcomes in a lipid-modifying trial: a meta-analysis of 330,376 patients from 47 landmark studies
Published in
Cardiovascular Diabetology, May 2015
DOI 10.1186/s12933-015-0226-z
Pubmed ID
Authors

Michel P. Hermans, Evariste Bouenizabila, Daniel K. Amoussou-guenou, Sylvie A. Ahn, Michel F. Rousseau

Abstract

Diabetes is a major cardiovascular risk factor. However, its influence on the rate of occurrence of cardiovascular (CV) events during a clinical trial that included a diabetes subgroup has not yet been quantified. To establish equations relating baseline diabetes prevalence and incident CV events, based on comparator arms data of major lipid-modifying trials. Meta-analysis of primary outcomes (PO) rates of key prospective trials, for which the baseline proportion of diabetics was reported, including studies having specifically reported CV outcomes within their diabetic subgroups. 47 studies, representing 330,376 patients (among whom 124,115 diabetics), were analyzed as regards the relationship between CV outcomes rates (including CHD) and the number of diabetics enrolled. Altogether, a total of 18,445 and 16,156 events occurred in the comparator and treatment arms, respectively. There were significant linear relationships between diabetes prevalence and both PO and CHD rates (%/year): y = 0.0299*x + 3.12 [PO] (p = 0.0128); and y = 0.0531*x + 1.54 [CHD] (p = 0.0094), baseline diabetes predicting PO rates between 3.12 %/year (no diabetic included) and 6.11 %/year (all patients diabetic); and CHD rates between 1.54 %/year (no diabetic) and 6.85 %/year (all patients diabetic). The slopes of the equations did not differ according to whether they were derived from primary or secondary prevention trials. Absolute and relative CV risk associated with diabetes at inclusion can be readily predicted using linear equations relating diabetes prevalence to primary outcomes or CHD rates.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 15%
Student > Master 4 10%
Student > Postgraduate 4 10%
Researcher 4 10%
Other 3 8%
Other 4 10%
Unknown 14 36%
Readers by discipline Count As %
Medicine and Dentistry 16 41%
Biochemistry, Genetics and Molecular Biology 4 10%
Nursing and Health Professions 1 3%
Computer Science 1 3%
Agricultural and Biological Sciences 1 3%
Other 2 5%
Unknown 14 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 May 2015.
All research outputs
#2,709,637
of 5,131,029 outputs
Outputs from Cardiovascular Diabetology
#206
of 446 outputs
Outputs of similar age
#98,132
of 172,491 outputs
Outputs of similar age from Cardiovascular Diabetology
#16
of 34 outputs
Altmetric has tracked 5,131,029 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 446 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 172,491 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.